Ben Upcroft

10.4k citations
115 papers · 6.5k · 4 hit papers · h-index 26

Impact in

Papers in

Ben Upcroft

114 papers receiving 6.3k citations

Ben Upcroft's Hit Papers

The limits and potentials of deep learning for robotics 2018 · 312 citations
3120+3+7Years since publication50010001.5k2.0k

Peers

Ben Upcroft
Comparison fields: 5 of 153
  • Computer Vision and Pattern Recognition 3.4k
  • Aerospace Engineering 1.9k
  • Analytical Chemistry 380
  • Plant Science 1.3k
  • Geology 193
Replace Juan Nieto with:
Juan Nieto Switzerland
Salah Sukkarieh Australia
Mingxing Tan United States
Simon X. Yang Canada
Peihua Li China
Qibin Hou China
Tom Duckett United Kingdom
Qilong Wang China
Edward Jones Ireland
Feras Dayoub Australia
Ben Upcroft relative to Juan Nieto Switzerland Juan Nieto's profile →
Citations per field
00.5×3.3×
Juan Nieto · 1×
Citations per year

Countries citing papers authored by Ben Upcroft

Since Specialization
Citations

This map shows the geographic impact of Ben Upcroft's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ben Upcroft with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ben Upcroft more than expected).

Fields of papers citing papers by Ben Upcroft

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ben Upcroft. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ben Upcroft. The network helps show where Ben Upcroft may publish in the future.

Co-authors

The 25 scholars most cited alongside Ben Upcroft, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ben Upcroft Line = papers co-authored together Ben Upcroft links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 115 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Simple online and realtime tracking
Hit paper breakdown →
20162319
2
DeepFruits: A Fruit Detection System Using Deep Neural Networks
Hit paper breakdown →
2016821
3
On the performance of ConvNet features for place recognition
Hit paper breakdown →
2015373
4
The limits and potentials of deep learning for robotics
Hit paper breakdown →
2018312
5 2001257
6 2015255
7 2017210
8 2017137
9 2016112
10 2016104
11 201793
12 201591
13 201685
14 201479
15 201671
16 201662
17 201461
18 201754
19 200634
20 201732

About Ben Upcroft

Ben Upcroft is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Artificial Intelligence, Plant Science and Computer Networks and Communications, having authored 115 papers that have together received 6.5k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (47 papers), Target Tracking and Data Fusion in Sensor Networks (22 papers), Advanced Image and Video Retrieval Techniques (22 papers), Advanced Vision and Imaging (17 papers), Smart Agriculture and AI (13 papers), Robotic Path Planning Algorithms (11 papers), 3D Surveying and Cultural Heritage (8 papers) and Remote-Sensing Image Classification (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (3.4k citations), Aerospace Engineering (1.9k citations), Analytical Chemistry (380 citations), Plant Science (1.3k citations) and Geology (193 citations). Ben Upcroft has collaborated with scholars based in Australia, United States and Switzerland. Frequent co-authors include Zongyuan Ge, Alex Bewley, Fábio Ramos, Lionel Ott, Feras Dayoub, Chris McCool, Tristán Pérez, Michael Milford, Inkyu Sa and Niko Sünderhauf. Their work appears in journals such as Journal of Field Robotics, Physical Review A, IEEE Robotics and Automation Letters, IEEE Transactions on Robotics and Nature.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact